Maintaining High SAP Data Quality is No Longer a Choice – it’s a Requirement

By Winshuttle Staff Blogger on Nov 22, 2017

In today’s digital world, do you know what the lifeblood of an organization is? It’s your data!!

Enterprise data drives critical operations and strategic business decisions around customer satisfaction, market growth, and bringing products to market. It’s the basis of all the intelligence and business processes you automate. As organizations rely on data more and more, having a data quality program is pivotal to ensure you achieve favorable business outcomes.

Data quality is always a moving target

If you’re thinking you don’t have a data problem, think again – every organization has data quality challenges and issues. The best way to find out what your challenges are is to talk to the users in your organization about how they work with data. Here are some common data issues related to products:

  • Not being able to find a material
  • Inability to list all similar parts together
  • Not understanding the material description
  • Getting away from free-format text purchasing
  • Not being able to match the PO to invoice. How will you pay the vendors?
  • having the requester choose the wrong GL account – again

Some of these might be considered petty issues, but if left alone, they could seriously impact bringing new products to market or revenue recognition, or result in high lost opportunity costs.

Let’s talk about customers

In a real-world scenario at a Telecom company, onboarding customer information was not being collected accurately. This meant:

High Data Quality

  • Accounts weren’t appropriately linked
  • Address postal codes were not correct
  • Promotional pricing wasn’t recognized
  • Communication type and frequency were not honored

A customer complained about a billing error after receiving their first bill. When you receive complaints regarding billing errors, you spend the time to research the correction, resolve the issue, and do what you can to make the customer happy.

An important thing to note here – customers generally only complain about overbilling. But if you’re overbilling, you’re almost certainly underbilling too. Since customers don’t complain about that, you’ve lost the opportunity to collect the revenue you’re due. These billing errors make it difficult to make a positive relationship with customers resulting in low customer satisfaction.

From a data quality ROI perspective, it’s important to look at gains in the moment and over time. Gains include inventory stock optimization, revenue improvements, process efficiencies, improved compliance and high customer satisfaction.

Businesses today need high quality data. It’s no longer a choice to make this a priority – organizations need to dedicate resources to improve data quality, as making decisions based on bad data can have substantial risks that result in negative business performance and high customer churn.

Contact us on to learn more about how Winshuttle can help you in your data quality journey!

About the author

Staff Blogger

The Winshuttle blog is written by professional thought leaders who are dedicated to providing content on a variety of topics, including industry news, best practices, software updates, continued education, tips and techniques, and much more.

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